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KDD
2005
ACM
218views Data Mining» more  KDD 2005»
14 years 7 months ago
A maximum entropy web recommendation system: combining collaborative and content features
Web users display their preferences implicitly by navigating through a sequence of pages or by providing numeric ratings to some items. Web usage mining techniques are used to ext...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
ITCC
2005
IEEE
14 years 1 months ago
A Web Recommendation System Based on Maximum Entropy
We propose a Web recommendation system based on a maximum entropy model. Under the maximum entropy principle, we can combine multiple levels of knowledge about users’ navigation...
Xin Jin, Bamshad Mobasher, Yanzan Zhou
AAAI
2006
13 years 8 months ago
Mixed Collaborative and Content-Based Filtering with User-Contributed Semantic Features
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
Matthew Garden, Gregory Dudek
RECSYS
2010
ACM
13 years 7 months ago
Recommending twitter users to follow using content and collaborative filtering approaches
Recently the world of the web has become more social and more real-time. Facebook and Twitter are perhaps the exemplars of a new generation of social, real-time web services and w...
John Hannon, Mike Bennett, Barry Smyth
WISE
2009
Springer
14 years 4 months ago
A Web Recommender System for Recommending, Predicting and Personalizing Music Playlists
In this paper, we present a Web recommender system for recommending, predicting and personalizing music playlists based on a user model. We have developed a hybrid similarity match...
Zeina Chedrawy, Syed Sibte Raza Abidi